Machine Learning Predicts Hepatocellular Carcinoma Risk

Researchers from RWTH Aachen and Technical University of Dresden published in Cancer Discovery (AACR) report a machine learning model that used UK Biobank data and external All of Us validation to predict hepatocellular carcinoma risk. A random-forest model combining demographics, electronic health records, and routine blood tests achieved AUROC 0.88, outperforming existing clinical scores. Simplified 15-feature version could enable broader primary-care screening, though prospective validation is needed.